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Registered Nurses’ Experiences with the Medication Administration Process

Hanna Pirinen, Lotta Kauhanen, Riitta Danielsson-Ojala, Johan Lilius, Ilona Tuominen, Natalia Díaz Rodríguez, Sanna Salanterä, Registered Nurses’ Experiences with the Medication Administration Process. Advances in Nursing 2015, 1–10, 2015.



Background. Registered nurses (RNs) have a role in the medication administration process (MAP) multiple times per day in a hectic hospital environment. This requires a great deal from the RNs in order to accomplish the demanding task of avoiding adverse drug events. However, the process has not been widely studied from the nurses’ perspective.
Aim. The aim of this study was to describe the different stages of MAP from the RNs’ perspective.
Methods. A qualitative descriptive research design, with a purposive sample involving thematic interviews of 20 RNs and questions to them in a paper form, was conducted in two medical units. Data was analyzed by using deductive content analysis.
Results. The results revealed that RNs confront numerous problems such as equivocal prescriptions, problems with information technology (IT), unavailability or incompatibility of the medicines, a substantial amount of generic substitutions, and changing medicine brands. Disruptions and distraction run through each stage of the MAP, excluding prescribing. The RNs desire support in all stages of the MAP.
Conclusion. There are areas to improve in each stage of the MAP from the RNs perspective. Real-time and ubiquitous documentation, along with software including the data and knowledge required in medication management, is needed.

BibTeX entry:

  title = {Registered Nurses’ Experiences with the Medication Administration Process},
  author = {Pirinen, Hanna and Kauhanen, Lotta and Danielsson-Ojala, Riitta and Lilius, Johan and Tuominen, Ilona and Díaz Rodríguez, Natalia and Salanterä, Sanna},
  journal = {Advances in Nursing},
  volume = {2015},
  publisher = {Hindawi},
  pages = {1–10},
  year = {2015},
  ISSN = {0161-9268},

Belongs to TUCS Research Unit(s): Turku BioNLP Group, Embedded Systems Laboratory (ESLAB)

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